Noise Filtering in Autonomous Emergency Braking Systems with Sensor Fusions

This paper discusses noise filtering in an autonomous emergency braking (AEB) system with a sensor fusion between a millimeter wave (MMW) radar and a camera. Three kinds of noise, namely twice harmonic noise, ground noise, and specular reflection noise, are then filtered. The former is caused by the reflection of a radar wave between a target object and the MMW radar; therefore, one of the sensing distances would be twice as longer as one of others. An object featuring this characteristic is treated as the noise and filtered. Next, detecting a ground metal as the target object generates the second noise with a focus of car-like objects. That is, an object-with the sensing distance from the MMW radar being smaller than that from the camera by a threshold value-is taken as the ground metal noise and ignored. Moreover, the third noise happens when there is a radar wave reflection between an object and its surroundings. While one focuses on standard derivation (SD) of a difference between the real and estimated object position from an object tracker, the specular reflection noise naturally reveals high SD. An object revealing this characteristic is hence removed from sensing data. Verification results indicate that the surroundings filtered by the proposed mechanisms are simplified such that the AEB system catches the right target object with its sensing distance being within [5, 50] (m) and our car speed lying within [10, 50] (km/h).